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New Technology of Library and Information Service  2016, Vol. 32 Issue (1): 73-80    DOI: 10.11925/infotech.1003-3513.2016.01.11
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Study on Construction of Domain Terminology Taxonomic Relation
Hui Zhu(),Jianlin Yang,Hao Wang
School of Information Management, Nanjing University, Nanjing 210023, China.Jiangsu Key Laboratory of Data Engineering and Knowledge Services, Nanjing 210023, China
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[Objective] Discuss how to obtain the terminology taxonomic relation from Chinese domain unstructured text. [Methods] Based on Digital Library domain text from CNKI, construct terminology hierarchy by terminology extraction, terminology Vector Space Model construction, BIRCH clustering and cluster tag distribution. [Results] Obtain the terminology taxonomic relation of Digital Library domain, and evaluate the effectiveness. The accuracy of clustering reaches up to 80.88%, and the accuracy of cluster tag extraction reaches up to 89.71%. [Limitations] Evaluate the effectiveness by random sampling, and in comparison with one method only. [Conclusions] Making use of BIRCH algorithm to construct terminology taxonomic relation, this algorithm has obvious advantage compared with K-means clustering method, and has higher execution and clustering effectiveness.

Key wordsTerminology      Taxonomic relation      Ontology      Ontology learning      Clustering     
Received: 19 June 2015      Published: 04 February 2016

Cite this article:

Hui Zhu,Jianlin Yang,Hao Wang. Study on Construction of Domain Terminology Taxonomic Relation. New Technology of Library and Information Service, 2016, 32(1): 73-80.

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